Big data presents organizations with a massive opportunity to generate new sources of value, providing evidence and content for the design of new products, new processes, and more efficient operations. To generate this value, data-driven organizations are leveraging sources they were never able to analyze before, such as machine-generated data, log files, and transcripts, in addition to traditional relational files. But simply having access to more data than ever before does not automatically lead to usable business insights. The data still needs to be wrangled—explored, structured, and cleansed—before it can be analyzed effectively.
The Royal Bank of Scotland serves over 30 million customers worldwide, and ensuring that they receive top-notch service is crucial for RBS’s business. Making use of big data—particularly unstructured and semistructured data from online customer web chats—allows RBS to understand the customer experience at all points of interaction with the bank and leverage that data to personalize and enhance their customer engagement processes.
Dan Jermyn and Connor Carreras discuss how data wrangling has enabled RBS to easily extract insights from unstructured data stored in Hadoop and dramatically decrease the time required to prepare data for analytics. Dan and Connor then describe specific big data wrangling techniques that can be used to support organizational analytics goals and explain how successfully leveraging big data can transform the customer experience.
Dan Jermyn joined the Royal Bank of Scotland in 2012. After stints in digital analytics and optimization, Dan is now driving new value streams for the bank and its customers as head of big data. A poacher-turned-gamekeeper, Dan learned his trade as a consultant and then head of analytics for an agency, where he led engagements with a host of major corporate and governmental organizations. In addition, he is a pioneer in digital marketing technology, having cofounded the SiteTagger platform, acquired by BrightTag (now Signal) in 2012.
Connor Carreras is Trifacta’s manager for customer success in the Americas, where she helps customers use cutting-edge data wrangling techniques in support of their big data initiatives. Connor brings her prior experience in the data integration space to help customers understand how to adopt self-service data preparation as part of an analytics process. She is a coauthor of the O’Reilly book Principles of Data Wrangling.
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